Special purpose analog processors are known in the art of machine vision for performing computationally intensive tasks such as edge detection and noise point removal. In a machine vision system with an array of photodetectors, an image can be focused directly onto the surface of the die. Other systems allow external data to be scanned in, as from an infrared focal-plane array, for example. Integrated sensor systems may include an array of photosensors and a low-power analog processor on a single chip. Such systems can be implemented on a VLSI chip using a standard CMOS process for low cost fabrication. Generally, these are compact, low cost, low power systems that accept raw image data and provide a digital output (such as an edge map), a processed gray-level image, or both.
Most conventional machine vision systems use gray-level imaging. However, the ability to process color information in machine vision systems and related applications is becoming increasingly important because there are tasks for which gray-level imaging alone is inadequate. Examples of such tasks include sorting objects based on color and detecting object boundaries while rejecting shadows and reflective glints.
A sought after "smart" machine vision system should be able to extract color information that is independent of individual pixel or scene brightness. Photodiodes having various response versus wavelength curves are available in standard CMOS and BiCMOS processes. Photodiodes with responses peaking at three different wavelengths are available with the BiCMOS process. These responses correspond to the junctions of a bipolar transistor, which are at various depths under the surface of a substrate. With a standard CMOS process, the well-substrate and heavily doped diffusions make at least two "colors" available. Color information can be extracted by taking the ratios of these photocurrents, to give information such as saturation and hue. Translinear circuits using MOS transistors operating in subthreshold have been built to compute these ratios.
Large random mismatch in current mirrors and related circuitry, especially with compact device dimensions, is a disadvantage of translinear circuits using MOS transistors operating in subthreshold. Photocurrent ratios from the various diodes are very modest, even for artificially constructed scenes with bright colors. Natural scenes tend to provide weak ratio signals among the large gray-level contrasts typically encountered. The achievable dynamic range (i.e., for color resolution) is very limited, especially with a circuit topology in which each raw photocurrent signal initially passes through a separate set of computational devices in a translinear network, as in the prior art. This is also true if current mirrors are used to perform weighted sums or differences of signals before generating ratios. This problem might be mitigated, at least in principle, using normalization or offset correction. Offset correction might be accomplished, for example, by using the difference signals of photocurrents to find a center point corresponding to a white pixel. This method, however, would require some means of programming or chopping with a reference scene. At the device level, colored films could be used to cover the photodiodes as is done with imaging arrays (as in regular video cameras, for example) to allow better discrimination. The effectiveness of this method would depend on the films and particular response curves available.
Because of the low photocurrent ratios from standard CMOS and BiCMOS photodiodes having different spectral responses and the fixed pattern noise introduced by device mismatches, there is a need for improved techniques of extracting color information in real time from a low cost photosensor imaging system.